Paper Title
AI and Social Media Moderation

Abstract
Therefore, due to the emerging of new social networks, the need for good management and content filtering to protect the user from hazardous information, and maintaining the proper language during communication, increases. Measures that can be employed when moderating contents in order to prevent undesirable occurrences include; AI and machine learning working with classification algorithms, and NLP. Therefore, the design and function of these systems are discussed in this paper as well as the problems of accuracy, size, and some ethical question, like the possibility of overcensorship and violated privacy. This also examines the resilience of existing models to adversarial examples that have been engineered to circumvent moderation systems. The paper also includes opportunities for the AI-deep moderation, based on the language and modality, more profound adversarial resistance, and /or combining human and AI moderation. It is also to integrate the element of ethical AI frameworks and the communication-transparency tools with the nature of AI, especially in fairness and bias categories. Therefore, to look into the details of the visions for further investigations and solutions to these challenges the AI in the content moderation can enhance the contribution to responsible and safer content on social media. Keywords - AI-powered content moderation, machine learning algorithms, natural language processing, social media safety, harmful content detection, adversarial attacks, ethical AI, realtime moderation, human-AI collaboration, multimodal content moderation, scalable AI systems, freedom of expression