Your organization operates an online message board, and in recent months, there has been a noticeable uptick in the use of toxic language and instances of bullying within the platform. To address this issue, you implemented an automated text classification system designed to identify and flag comments that exhibit toxic or harmful behavior. However, you've received reports from users who believe that benign comments related to their religion are being incorrectly classified as abusive. Upon closer examination, it's become evident that the false positive rate of your classifier is higher for comments that pertain to certain underrepresented religious groups. Given that your team is operating on a limited budget and already stretched thin, what steps should you take to remedy this situation?