Dr Louise Marie Hurel
As frontier AI models expand in their capability and application, it is key that their evolution remains grounded in safety and security safeguards. Proactive safeguarding is essential to prevent them from being misused or repurposed by malign state or criminal actors to conduct cyber-attacks, terrorist attacks, and other harmful activities.
Third-party evaluation of frontier AI models is increasingly recognised as essential to safety and security—by developers, governments, and regulators alike. Yet enabling meaningful external evaluation requires granting access to some of the most sensitive intellectual property in tech/AI sector. The security risks associated with this access—from intellectual property leakage to model compromise to exploitation by state-sponsored actors—remain poorly mapped and inadequately standardised. This gap stifles the evaluation ecosystem—one where developers restrict access out of security concerns, while evaluators lack the information they need to conduct effective assessments.
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