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AI and Biorisk: An Explainer
By Stephanie Batalis. PhD (sb2132@georgetown.edu)
Recent government directives, international conferences, and media headlines reflect
growing concern that artificial intelligence could exacerbate biological threats.
When
it comes to biorisk, AI tools are cited as enablers that lower information barriers,
enhance novel biothreat design, or otherwise increase a malicious actor’s capabilities.
It is important to evaluate AI’s impact within the existing biorisk landscape to assess
the relationship between AI-agnostic and AI-enhanced risks. While AI can alter the
potential for biological misuse, focusing attention solely on AI may detract from
existing, foundational biosecurity gaps that could be addressed with more
comprehensive oversight.
Policies that effectively mitigate biorisks will also need to account for the varied risk
landscape, because safeguards that work in one case are unlikely to be effective for all
actors and scenarios. In this explainer, we outline the AI-agnostic and AI-enhanced
biorisk landscape to inform targeted policies that mitigate real scenarios of risk without
overly inhibiting AI’s potential to accelerate cutting-edge biotechnology.
Our key takeaways regarding AI and biorisk include:
1. Biorisk is already possible without AI, even for non-experts. AI tools are not
needed to access the foundational information and resources to cause biological
harm. This highlights the need for layered safeguards throughout the process,
from monitoring certain physical materials to bolstering biosafety and
biosecurity training for researchers. The recent Executive Order on AI’s
requirement to screen DNA synthesis for federally-funded research is an
example of a barrier to material acquisition.
2. The biorisk landscape is not uniform, and specific scenarios and actors should
be assessed individually. Distinct combinations of users and AI tools impact the
potential for harm and the most effective likely policy solutions. Future
strategies should identify clearly defined scenarios of concern and design
policies to target them.
3. Existing policies regarding biosecurity and biosafety oversight need to be
clarified and strengthened. AI-enabled biological designs are digital
predictions that do not cause physical harm until they are produced in the real
world. Such gain-of-function research, which modifies pathogens to be more
dangerous, is already the target of existing policies.
