AI vs. Toxicity: Battling Online Harm with Automated Moderation

The article discusses the use of AI-powered content moderation in social media platforms to combat online harm, such as graphic violence, hate speech, and harassment. It explains how autonomous content moderation systems use machine learning algorithms trained on large datasets to analyze and recognize patterns in language and classify content. The process is more complicated when audio and video elements are added, requiring speech-to-text conversion, contextual analysis, computer vision, generative adversarial networks (GANs), and optical character recognition (OCR). Sentiment analysis is also important for deciphering nuances in tone and context. The societal implications of AI content moderation include reducing mental health issues among human moderators and addressing the risk of replicating real-life biases and discrimination with AI-powered moderation models.