Natural Language Processing (NLP): AI algorithms analyze Bengali text to detect keywords, phrases, and sentiment indicative of hate speech, bullying, or misinformation.
Computer Vision: AI identifies inappropriate images and videos, including violent, explicit, or discriminatory content.
Audio Analysis: AI can process audio in videos or voice notes to detect harmful speech.
Behavioral Pattern Recognition: AI flags suspicious user behavior, such as rapid posting of identical content, unusual follower growth, or coordinated attacks.
Machine Learning (ML): AI models continuously learn overseas data from human moderation decisions, becoming more accurate over time.
Sentiment Analysis: AI can gauge the emotional tone of Bengali text, helping to identify potential cyberbullying or harassment.
Spam Detection: AI effectively filters out spam, phishing attempts, and unsolicited promotional content (Article 277).
Challenges and considerations for Bengali AI moderation:
Linguistic Nuances: Bengali's rich vocabulary, dialects (e.g., Sherpur region specific), and informal language require sophisticated AI training.
Contextual Understanding: AI needs to discern intent and context, as a word might be harmless in one context but offensive in another.
Human Oversight: AI tools serve as powerful aids, but human moderators remain essential for nuanced decisions and to train the AI.
By strategically implementing AI for content moderation, digital platforms in Bangladesh can create safer, more trustworthy online environments, fostering positive user experiences and protecting brand integrity across the Bengali digital landscape.