There is still room for improvement in NSFW AI, and there are a few indications that this progress is coming along nicely. Researchers have observed that the accuracy of AI models has improved by more than 20 percent each year since 2023 in terms of identifying explicit content. As an example, Facebook, YouTube and other platforms have developed their systems to better determine whether images and videos are graphic or not while producing fewer false positives. That improvement is based on training models with more diverse datasets so that AI systems can comprehend different kinds of explicit content, even niche and less-traditional variations. It has also updated its ability to find inappropriate content in text form, meaning the success of identifying hateful speech is up 25% in two years.
A prime example of this is the work taking place with companies such as Google who have spent millions developing its adult content detection AI tools. As per a report from earlier this year, Google said that due to its AI model flagging over 85% of harmful content before it reaches human reviews in 2022, had surpassed what was possible with previous models. The improvement in performance is attributed to the AI’s selected not specific images, but also context-sensitive words that help it filter offensive material better than before.
Additional advancements, such as improving NSFW AI’s contextual comprehension capability will also be critical. AI finds it hard to differentiate between illicit and legitimate material like educational content or art. And according to research from the University of Tokyo in 2021, one of the greatest challenges faced is training AI to recognize intent and context in less obvious text. In short, though current models are very performant (when task-based), they often lack fine-grained data related to context that helps determine the intent behind display images or videos. One such example is, in 2020 Instagram AI flagged a post on sexual health as explicit despite being an educational post, and that cannot happen unless the system has improper training continuously.
Furthermore, the combination of Reinforcement Learning and even Deep Learning algorithms to improve these systems will only have a positive impact on their decision-making capabilities. One major potential avenue for enhancing NSFW AI is through reinforcement learning, in which AI systems learn to perform better when subjected to real-time feedback. That same year, for example, a report from the content moderation firm Spectrum Labs showed that AI models trained with reinforcement learning were up to 30 per cent more accurate than such traditional supervised learning models.
In the end, the advancements of NSFW AI depend on repetition, high-quality data, and sensitive algorithms that can stride through convoluted realities. The future of NSFW AI looks bright with even more advanced content filtering making the internet a much safer place. Check nsfw ai to find out how can we improve on these?