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ZDNET's key takeaways
New research shows how fragile AI safety training is.
Language and image models can be easily unaligned by prompts.
Models need to be safety tested post-deployment.
Model alignment refers to whether an AI model's behavior and responses align with what its developers have intended, especially along safety guidelines. As AI tools evolve, whether a model is safety- and values-aligned increasingly sets competing systems apart.
But new research from Microsoft's AI Red Team reveals how fleeting that safety training can be once a model is deployed in the real world: just one prompt can set a model down a different path.
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"Safety alignment is only as robust as its weakest failure mode," Microsoft said in a blog accompanying the research. "Despite extensive work on safety post-training, it has been shown that models can be readily unaligned through post-deployment fine-tuning."
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