AI-Driven Automated Content Moderation: Balancing Accuracy and Bias in Social Media Platforms
Keywords:
AI, Content Moderation, Social Media, Bias, Accuracy, Algorithmic Fairness, Ethics, Author Name, Scopus, Springer, Journal Name, Wissira, Journal Short Form, Wissira Press, Wissira Research Lab, Research Gate, SSRN, ISSN, Academia, UGC Care, PubMed, WOSAbstract
The rapid proliferation of social media platforms has led to the widespread dissemination of user-generated content, making content moderation a critical concern. Automated content moderation using Artificial Intelligence (AI) offers the potential to efficiently manage vast amounts of data, but it also raises challenges related to accuracy, bias, and ethical implications. This study explores the use of AI in content moderation, focusing on balancing the accuracy of content filtering with the risks of inherent biases in algorithmic decision-making. We review existing AI models, methodologies, and their impact on the moderation process in social media environments. Additionally, we propose frameworks for improving the effectiveness and fairness of AI-driven moderation systems while ensuring transparency and user rights. The study's findings suggest that while AI can significantly enhance moderation efficiency, addressing algorithmic bias and ensuring human oversight remain paramount.
