According to Sam Nunn, a developer with OpenAI Researchers The development raises questions for content moderation across platforms. Moderators have a hard time detecting and handling such content since AI-generated porn is getting really convincing. Platforms using standard methods of moderation experienced a 40 percent spike in NSFW content evading filters as AI-generated media changed at an escalating rate, the report forecasted for 2023. This trendline elevates the urgency of sophisticated moderation strategies to remain ahead in this battle.
But the difficulty of moderating AI-generated content comes in how realistic it is, and possibly just as quickly its production might come. Traditional moderation tools might be developed to identify one of these patterns or special single phrases, but NSFW AI can beat this type filter with its flexible output that generates thousands — even millions — realistic photos and videos. Industry insiders suggest referees mistakenly called as compliant upon current detection systems can only verify approximately 70% of the flagged content in Year2022. This failure rate demonstrates the need for AI-based moderation technology to understand context and recognize subtle media signals.
Twitter and Reddit have already started using AI moderation systems to handle inappropriate content. Scanning text, images and videos for NSFW meta-data (NSFW vs SFW) is something these systems are capable of doing hundreds or even thousands time per second (^)(^). Using machine learning for these tools allows them to detect inappropriate content with up to 95% accuracy, an improvement from the usual manual moderator's rate of about 70%. With a 73% increase in efficiency, this not only creates less risk of exposing bad content but also reduces moderation costs by almost half — an advantage for such a solution that scales on large platforms.
But NSFW AI moderation tools come with ethical considerations. Critics of the bill argued that heavy use of AI for content moderation can result in over-censorship and false positives even. Take the example of 2022, Meta had its AI unknowingly identified image contents to be inappropriate with more than a 10% mistake in artistic content as nudity seen on pageantry if classified that way or city affairs pictures assuming there were some kind of explicit material involved. It encapsulates the tightrope walk AI systems have to do: keeping content in check without impinging on free speech.
Consider moderation in a time of deepfakes I mean, AI has already been leveraged to create deepfake pornography in NSFW environments by taking faces and putting them on explicit videos. This focus on regulation will have real world implications for the deepfake problem: a 2023 study showed that more than 95% of all online deepfakes were pornographic, creating substantial obstacles to platforms seeking ways in which they can curtail this. It gets worse: The legal consequences of deepfake porn are just as problematic, given that victims have few avenues for redress in the absence of comprehensive legislation on AI-generated content.
As Tech leaders, including Tim Cook have observed that ethical AI development must be made a priority since "as lab researchers advance in their use of Ai, we need to assure they prioritize using it responsibly for the good especially where its application touches humans rights and lives". The sentiment reflects a broader move by the industry to build AI systems that have better powers of discrimination and can tell right from wrong more acutely without violating users' rights.
nsfw ai moderation tools provide a scalable solution for businesses and platforms with user generated content (UGC) sites which in turn will enable them to handle an ever-increasing stream of material that is mature. We can probably expect that to evolve as the technology improves — and ends up focusing on improving accuracy and context, resulting in better content management with lower risks of false positives (overcensorship) or user backlash.
