What are some potential risks of using BERT?
There are potential risks associated with using BERT. Some of these risks include :
Bias : BERT and other language models have been shown to amplify biases that exist in the training data. This can lead to unfair or discriminatory outcomes in natural language processing applications, such as biased language in chatbots or automated text summarization.
Privacy : Because BERT and other language models are trained on large amounts of data, there is a risk that sensitive or private information could be included in the training data and inadvertently revealed by the model.
Security : BERT and other language models can be vulnerable to adversarial attacks, where an attacker modifies the input to cause the model to make incorrect predictions. This could be used to cause harm in applications such as automated content moderation or spam detection.
Dependence : There is a risk that as BERT and other language models become more prevalent in natural language processing applications, developers and users may become overly reliant on them and fail to recognize their limitations or potential biases.
