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Abstract: Social media and other large online communication venues allow users to express themselves freely and occasionally anonymously. While having the right to express oneself freely is a value-laden human right, inciting and disseminating hatred against another group is a misuse of this freedom. The HS detection pipeline starts with the dataset gathering and preparation stage. Social media sites like Face book, YouTube, Twitter, and others are often used to collect data. Pre-processing is done in accordance with the quality and structure of the dataset. The artificial intelligence plays important role for the hate speech detection. The artificial intelligence based techniques is designed in the last years for the hate speech detection. In this paper various techniques for hate speech detection is reviewed and analysed in terms of various parameters. Key Word: Artificial Intelligence, Hate Speech Detection, Data Labelling. References [1] N. Shawkat, J. Simpson and J. 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