Frontier risk and preparedness

As part of our ‘unknown unknowns’ work stream from the Preparedness Framework⁠(opens in a new window), the Preparedness Team offered $25K each in API credits for the ten best submissions to the Preparedness Challenge. These submissions aimed to identify unique, but still plausible, risk areas for frontier AI. We received hundreds of submissions in half a dozen languages and are excited to announce our ten winners below. This exercise helped us surface new types of risk, so that we can improve our preemptive testing and mitigation strategy.

We reviewed and graded each submission by assessing technical rigor, uniqueness, scale of potential damage caused, and clarity. The top ten submissions, some of which are listed below, combined thoughtful ideas with proofs of concepts, and highlighted the advantages of their approach over an approach that did not utilize AI-related tools¹.

• Precipitating a financial crisis in a strategically important country - Claudia Biancotti 

• Identifying private information discussed or released in public settings - Chris Cundy 

• Increasing the likelihood of reverse-engineering classified or sensitive information - George Davis 

• Impeding individuals’ ability to access medical care - Mato Gudelj

• Identifying targets for blackmail and scams - Connor Heaton 

• Causing plane crashes by accessing radio frequencies and disrupting flight paths - Joel Hypolite 

• Running prompt injection attacks to elicit dangerous responses - Daniel Julh

• Operating and scaling cyberattacks that break victims’ computers and request payments for restoration of functions - Jun Kokatsu

• Interfering with patient’s medical dosage - Zhenzhen Zhan