NSFW AI chatbot systems (not-safe-for-work) are dedicated to identifying harmful/coded content and filtering it out of the conversation. A study found that in 2023, the AI models trained on datasets of textual information could successfully identify over 85% of NSFW-related coded language like slang, abbreviations, and euphemisms. The use of coded phrases is especially problematic for AI, as indirect language and culturally specific references are often unclear in context – making it nearly impossible for the system to tell if a particular group communication is harmless or harmful. One classic example of a coded phrase is an acronym or deliberately misspelled writing, e.g., "wyd" (what you doing), or "lulz" (laughing out loud) that can be used in chat-text to pretend possible indecent substance.
Machine learning algorithms are the backbone of all AI systems that studies words data and develops patterns to create correlations between different words and phrases. They are stuck in thousands of learned samples (in a supervised manner) of explicit versus coded conversations. And so, processing this data helps the AI learn to recognize context — like a phrase that on its own might seem innocuous, but in practice is clearly othering or offensive because it signals to the user they are not welcome in some way. According to Stanford University, AI could auto-detect 75% of all newly coined phrases within a month of the phrase being introduced due to its rapid data updates and retraining protocols (Stanford, 2022).
Also, how well AI can detect coded phrases is dependent upon the strength of its natural language processing (NLP) abilities. NLP enables the AI to learn the syntax and semantics of a dialogue, making it possible for it to recognize coded language. However, in advanced cases where the users alter their phrases with the help of symbols and replace-average-letter to find a path into CSAM detection is challenging. As an illustration, one of the freshest news about online social media platform showed that the AI moderation system was unable to identify covert references to NSFW material — numbers or symbols instead of letters (h4ck3r vs. hacker). Many other times, an AI system has to rely on much more advanced methods like semantic analysis to identify what a phrase actually means and understand its context.
To tackle this problem, a few companies have created hybrid models that utilize rule-based detection as well as machine learning. To enhance the ability of the AI to spot coded language, a hybrid approach can be employed by combining a set of fixed rules for identifying known slang and abbreviation with machine learning that is trained on novel patterns. One example from a top AI service in 2023 claimed that its hybrid approach identified 98% of the coded language deployed on its platform within hours of insertions.
However, nsfw ai chat systems are still struggling with very fine grained, nuanced, and coded wordings. One possibility is that AI models may miss contextual drift; this would serve as a limitation for real-time conversations, in which phrases may take on different meanings depending on the subject or sentiment. According to the great AI researcher Dr. Fei-Fei Li, "The subtleties and nuances of human communication continue to elude A. I”, especially humor, sarcasm or coded language."
In general, AI systems are becoming more capable of spotting subtle coded phrases, but ultimately whether such phrasing can be identified or filtered is determined by the underlying model and its training, as well as the data on which it was trained. As the language processing and pattern recognition capabilities of AI continue to develop, its effectiveness in identifying even the subtlest coded rubbish will become ever more assured. Learn how AI can identify and remove indecent content at nsfwai chat.