The UK AI Safety Institute (AISI) has published a blog article outlining the role of third-party evaluators in ensuring AI safety and thereby fostering transparency and trust among stakeholders and the wider public. AISI stresses that while the science of model evaluations is still developing, they cannot yet provide definitive safety certifications; however, such evaluations can still lead to safety improvements.
The blog examines the need for a structured framework for testing frontier AI systems, highlighting the importance of both pre- and post-deployment evaluations to identify potential risks, especially during significant system updates. It discusses what should be tested—such as misuse risks, societal impacts, the functioning of autonomous systems, and the robustness of safety mechanisms—while also aiming to establish a methodology to identify which systems merit evaluation.
The AISI also notes the need for an ongoing debate within the scientific community to refine testing practices and methodologies in response to evolving AI technologies.
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