The NSFW AI (Not Safe For Work Artificial Intelligence) are different across the platforms beacuse of their technology, policies and there by effectiveness. NSFW AI models differ greatly in their accuracy and how they work which can make a large difference when trying to use it for content filtering.
For example, sites like YouTube use a mixture of machine learning algorithms and human moderators to identify NSFW content. YouTube: The platform uses deep learning models which are trained with large dataset to detect the content that should not be posted this system can correctly identify explicit material and has 90% accuracy rate in detecting such videos/films. In addition to algorithmic detection, the platform employs a team of over 10,000 content moderators who review flagged videos and make final judgments.
On the other hand, social media platforms like Facebook and Instagram take a different route. Facebook uses object recognition and natural language processing to recognize pornographic images and text with its NSFW AI. This ranges from relatively successful detections of nudity or hate speech and very many more inappropriate forms. Facebook's AI flagged around 98% of hate speech before being reported by users in a report that will appear on the year 2023, but there were problems with NSFW content too -- only about 70% of flagged pictures and videos really went against guidelines.
Twitter, on the flip side relies more so on reports and community moderation. Although Twitter does employ AI as part of its broader efforts to identify harmful content, its system is still largely reliant on user flags and human moderators for enforcement. However, relying on an AI model is essentially a double-edged sword as there are risks of uneven content removals if the use-case in context has subtleties that human moderators might read and understand better with innate life skills.
MeetMe enables several AI systems that circumstances demand in adult content platform to access them just like dating apps do, use the kind of advanced filtering algorithms suitable for a need. An instance: a dating app could uses image recognition algorithms to check for nudity in profile pictures or messages, configurable by the users. Most of these systems are less public but can be equally useful because they focus intently on a specific task.
In general, NSFW/AI techniques are implemented in a variety of ways and range greatly across platforms based on their technical capabilities, policies to the technology solution they offer with dependences on human oversight. Different AI performance and moderation practices lead to varying user experiences, content control levels.
Learn more at nsfw ai.