In a candid discussion, Dario Amodei, CEO of AI research company Anthropic, has highlighted the intrinsic unpredictability of artificial intelligence (AI) models, emphasizing that complete assurance of their safety is unattainable.
Drawing parallels between AI behavior and human unpredictability, Amodei stated, "It's just like, if I think of you or me, if I'm like the quality assurance engineer for you or me, can I give a guarantee that a particular kind of bad behavior you are logically not capable of will never happen? People don't work that way."
He elaborated on the challenges of pre-deployment testing, noting that while rigorous evaluations are conducted, including collaborations with government AI safety teams, these measures cannot fully predict how models will behave once exposed to real-world scenarios. "You can test ahead of time... But the hard truth is that there's no way to be sure. They're not like code where you can do formal verification. What they can do is unpredictable," Amodei explained.
Amodei emphasized the importance of continuous monitoring post-deployment, acknowledging that unforeseen applications—both beneficial and harmful—often emerge only after widespread use. "Just as every time we release a new model, there are positive applications for it that people find that we weren't expecting... I expect there also to be negative applications," he remarked.
These insights underscore the complex challenges faced by AI developers and policymakers in ensuring the safe deployment of increasingly sophisticated AI systems. As AI continues to integrate into various aspects of society, Amodei's reflections serve as a reminder of the need for ongoing vigilance and adaptive strategies to mitigate potential risks.
Source: https://officechai.com/ai/theres-no...f-ai-model-safety-anthropic-ceo-dario-amodei/
Drawing parallels between AI behavior and human unpredictability, Amodei stated, "It's just like, if I think of you or me, if I'm like the quality assurance engineer for you or me, can I give a guarantee that a particular kind of bad behavior you are logically not capable of will never happen? People don't work that way."
He elaborated on the challenges of pre-deployment testing, noting that while rigorous evaluations are conducted, including collaborations with government AI safety teams, these measures cannot fully predict how models will behave once exposed to real-world scenarios. "You can test ahead of time... But the hard truth is that there's no way to be sure. They're not like code where you can do formal verification. What they can do is unpredictable," Amodei explained.
Amodei emphasized the importance of continuous monitoring post-deployment, acknowledging that unforeseen applications—both beneficial and harmful—often emerge only after widespread use. "Just as every time we release a new model, there are positive applications for it that people find that we weren't expecting... I expect there also to be negative applications," he remarked.
These insights underscore the complex challenges faced by AI developers and policymakers in ensuring the safe deployment of increasingly sophisticated AI systems. As AI continues to integrate into various aspects of society, Amodei's reflections serve as a reminder of the need for ongoing vigilance and adaptive strategies to mitigate potential risks.
Source: https://officechai.com/ai/theres-no...f-ai-model-safety-anthropic-ceo-dario-amodei/