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Paedophiles are using AI to create and share images of child pornography | #childsafety | #kids | #chldern | #parents | #schoolsafey

The increasing prominence of an AI-powered internet is becoming more evident. Unfortunately, though reality can be both unsettling and harmful, especially when we consider how AI is being misused by certain bad elements, like paedophiles.

A recent report by The Washington Post reveals that AI image generators are now being utilized to produce and distribute significant amounts of child sexual abuse material (CSAM).

What makes matters even worse is that the proliferation of such material could potentially hinder the efforts of law enforcement in aiding the victims.

Identifying victims is not easy
Rebecca Portnoff, the director of data science at Thorn, a non-profit organization focused on child safety, expressed her concerns. She explained that children’s images, including those of known victims, are being repurposed for nefarious purposes. Portnoff further stated that there has been a continuous increase in the use of AI-generated CSAM since the previous autumn.

“Children’s images, including the content of known victims, are being repurposed for this really evil output,” Rebecca Portnoff said.

Identifying victims is already an extremely challenging task for law enforcement, akin to finding a needle in a haystack when attempting to locate a child in danger. Portnoff emphasized that the accessibility and realistic nature of these AI tools have significantly compounded the difficulties faced by law enforcement, making their job even more demanding.

Using AI to beat CSAM filters
CSAM or child sexual abuse materials are normally filtered out by AI generators, using filters created just for that. However, predators have found a way around it. The report indicates that the majority of predators are utilizing open-source image generators, specifically Stability AI’s Stable Diffusion model, to generate unsettling content, as well as Midjourney.

Although Stable Diffusion does incorporate certain safety measures, such as a filter to identify CSAM, the report highlights that these filters can be easily bypassed with the appropriate knowledge and a few lines of code.

Detecting and identifying such images poses a challenge. Current systems designed to combat CSAM were primarily developed to detect the dissemination of known images, rather than newly generated ones. As a result, the existing mechanisms may struggle to effectively address this emerging issue.

A community of AI-assisted sexual abusers
The news presents alarming aspects on multiple fronts. It is deeply disturbing to witness individuals known for engaging in harmful activities sharing information and techniques on online forums, and exploiting the emerging technology to indulge in abusive and illegal fantasies.

Furthermore, this recent discovery aligns with a larger and more concerning pattern of AI-assisted sexual abuse, highlighting the growing trend.

It serves as a distressing reminder of the potential for synthetic content to inflict genuine harm in the real world. In this particular instance, the consequences are inflicted upon the most vulnerable members of society, exacerbating the gravity of the situation.

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