As fears of voyeurism have grown in recent years, it has spiraled into a popular theme with Artificial Intellegence (AI). The AI field dealing with nsfw content has complex algorithms and data processing mechanisms. They work with large datasets often — for example, a nsfw ai service may process terabytes of data regularly to train their models.
The primary point of interest for privacy in NSFW AI is what kind of data handling practices are used. As the GDPR — General Data Protection Regulation in Europe gets effectued, companies need to make sure more than ever that personal data is processed with explicit consent. Under GDPR, a system responsible for handling risky content should undertake certain principles like Anonymization of data and user consent flows. For example, companies like OpenAI must put in place measures to safeguard user data (such as anonymisation and encryption of personal information or safe storage thereof).
This is an ongoing debate that has reared its head in a real-world example as recently as 2021, when the sheer handling of user data came into question from one major tech company using it within their AI systems. The incident damaged user trust dramatically and triggered a flood of regulatory reviews aimed to highlight the essential role that privacy protection has in an AI-oriented application.
Transparency is something privacy professionals tend to harpoon against in the context of AI. As cyber security guru Bruce Schneier says, “the only way to own your data is if no-one else can see it.” Similarly, this rule supports our requirement to motivate the company to inform its data processing principles openly in order for users not only to give trust but be more likely keep it.
Suggestive/Lewd in AI systems usually have a headache when combining this with due compliance to privacy. As one example, the inclusion of user-generated content into training datasets should be handled with caution so as to prevent inadvertent disclosure of PII. It is up to companies now to provide strong data protection in order that unauthorized access cannot occur and, likewise the data only be used for its intended purposes.
Current developments in nsfw ai technologies are proof of the industry marching forward to defend user privacy. For instance, companies are exploring cutting edge privacy-preserving technologies such as differential-privacy and federated learning to limit data exposure while enabling AI systems.
However, fears remain and efforts are ongoing. The regulatory bodies and government reviewers are also working on this to make sue that all the practices of AI companies meet up with requirements regarding privacy. Over the course of this development, we keep our focus on securing user privacy. We are consistently discussing with other teams in nsfw.ai how to best achieve it.