The Role of AI in Moderating Online Hate Speech: A Discourse Evaluation

As people spend more time online, hate speech on social media and other digital channels has grown into a big problem for everyone. Because of this, a lot of tech companies have started to use systems that use artificial intelligence (AI) to find, screen, and limit harmful materials. The goal of this study is to find out how AI can help police stop hate speech online by looking at how these technologies affect, change, and sometimes confuse digital communication. It is easy and quick for AI to solve problems, but it often has trouble with the complicated rules of language that people use, like humor, metaphor, cultural context, and new terms. People are worried about both too much and too little filtering, which means that legal speech is being taken away and hate speech that is secret or coded is not being found. CLA and computational linguistics are used in the study to look at real-life data sets of conversations that AI listened to on public platforms like Twitter and YouTube. This study looks at how AI tools for tracking find hate speech, how often they get it wrong based on the context, and how automatic police changes the way people talk to each other. It also looks at aggressive speech, which is when people change the way they talk to avoid getting caught. "Mixed-methods" are used in the study to look at AI's ability to be flexible and its effect on sociolinguistics. This includes both giving content that has been flagged a number mark and judging the quality of speech.