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Description

A new artificial intelligence system has been developed to detect and respond to child sexual abuse material more efficiently, aimed at protecting victims at a faster rate. Utilizing real CSAM data, this AI effectively scans, identifies, and flags new images that depict child abuse with remarkable precision. In partnership with law enforcement and prominent Canadian universities, CEASE.ai employs a combination of neural networks and various AI models to achieve accurate detection of such harmful content. The system offers investigators a user-friendly plugin that allows them to upload images from their cases and run hash lists to filter out known content. Subsequently, the AI suggests potential labels and prioritizes images that may contain previously unseen CSAM. Investigators can then examine the flagged images, verify their illegal nature, strengthen their cases against perpetrators, and expedite the rescue of vulnerable victims. Additionally, social media platforms integrate with the CEASE.ai API endpoint, which processes all user-uploaded images in real time, ensuring that any content related to child abuse is swiftly identified and labeled by the system. This innovative approach not only enhances the efficiency of investigations but also contributes significantly to the protection of children at risk.

Description

Safer is designed to combat the viral dissemination of child sexual abuse material on your platform, ensuring enhanced safety for your team, organization, and users alike. This system not only boosts team efficiency and well-being but also fosters collaboration by dismantling silos and tapping into community expertise. Utilizing advanced perceptual hashing and machine learning algorithms, it effectively identifies both known and unknown CSAM. Flagged content can be queued for review through moderation tools specifically developed with employee wellness as a priority. Verified CSAM is reviewed and reported, with content securely archived to meet regulatory standards. Additionally, Safer expands protective measures to detect both known and potentially new or unreported content at the point of upload. The Safer community collaborates to discover more abuse materials, and our APIs are engineered to enhance the collective knowledge surrounding child abuse content by sharing hashes, comparing with industry-standard hashes, and providing input on false positives. This collective effort not only strengthens the fight against abuse but also encourages a proactive approach to safeguarding vulnerable individuals.