The recent RAND report concludes that current Large Language Models (LLMs) do not significantly increase the risk of a biological attack by non-state actors. Their research, conducted through a red-team exercise, found no substantial difference in the viability of plans generated with or without LLM assistance. However, the study emphasized the need for further research due to the rapid advancement of AI technology. The potential risks associated with superintelligent AI remain a point of concern.
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RAND Report: AI and Biological Attack Risk
Summary
A recent report from RAND has found that current Large Language Models (LLMs) do not significantly increase the risk of a biological attack by non-state actors. This conclusion was reached after a red-teaming exercise to assess the potential use of LLMs in planning such attacks.
Key Findings
The study revealed that the use of LLMs did not result in a statistically significant difference in the viability of attack plans compared to those developed without LLM assistance. In fact, plans developed with LLMs were marginally less viable. This suggests that LLMs do not provide substantial advantages in this context.
Implications
While the current generation of LLMs may not pose a significant risk in facilitating biological attack planning, the report emphasizes the need for ongoing research. As AI technology advances rapidly and becomes more accessible, it is crucial to understand and address potential risks associated with emerging AI tools.
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List of Useful Links:
- AI Lab in Telegram @aiscrumbot – free consultation
- RAND report says LLMs don’t increase risk of biological attacks
- DailyAI
- Twitter – @itinaicom
