Security News > 2023 > September > 3 ways to strike the right balance with generative AI
In the context of generative AI, having properly defined user roles to control who can access the AI system, train models, input data, and interpret outputs has become a critical security requirement.
You might grant data scientists the authority to train models, while other users might only be permitted to use the model to generate predictions.
During their training phase, AI models can be vulnerable to attacks designed to exploit and disrupt the training process.
Such threats might involve introducing subtly altered inputs into the system crafted to mislead the AI model into making incorrect predictions or decisions.
Since many AI models leverage user feedback to improve the model's accuracy, there's a real risk that bad actors can manipulate this feedback mechanism to alter the model's predictions for malicious purposes.
Perhaps the greatest challenge posed by AI models is their potential to function as "Black boxes," with their inner workings shrouded in mystery.