Experts warn that artificial intelligence could facilitate the normalization of child sexual abuse as explicit images proliferate on the internet.

Artificial intelligence advancements have brought about a concerning trend of creating realistic and explicit images of children in sexual situations. This worrying development may lead to an increase in real-life sex crimes against children, according to experts. The popularity of AI platforms that can imitate human conversation or generate realistic images has skyrocketed since the release of the chatbot ChatGPT, marking a significant moment for the use of AI.

While many people have been intrigued by this technology for work or academic purposes, others have adopted it for more malicious intentions. The UK’s leading law enforcement agency, the National Crime Agency (NCA), has recently issued a warning about the proliferation of machine-generated explicit images of children, which they believe is “normalizing” pedophilia and disturbing behavior towards kids. Graeme Biggar, the NCA’s director general, emphasized that the viewing of such images, whether AI-generated or real, significantly increases the risk of offenders transitioning to sexually abusing children themselves.

The NCA estimates that in the UK, there are approximately 830,000 adults, or 1.6% of the adult population, who pose some form of sexual threat to children. This figure is ten times higher than the country’s prison population. According to Biggar, the majority of child sexual abuse cases involve the consumption of explicit images. With the aid of AI, the creation and consumption of sexual imagery could normalize the abuse of children in the physical world.

On a global scale, a similar surge in using AI to generate sexual images of children is underway. Rebecca Portnoff, the director of data science at Thorn, a nonprofit organization dedicated to protecting children, pointed out that children’s images, including those of known victims, are being repurposed for nefarious purposes. This availability of AI tools, coupled with the realism they achieve, adds significant complexity to the already challenging task of victim identification for law enforcement agencies.

While some AI platforms have guidelines preventing the creation of disturbing images, individuals with malicious intent have been known to explore workarounds in order to generate explicit content. This poses a tremendous challenge for authorities in distinguishing between fake AI-generated images and those of actual victims in need of assistance.

Furthermore, AI-generated images can be exploited in sextortion scams, as highlighted by the FBI in a recent warning. Deepfakes, which involve manipulating videos or photos of individuals to make them appear as someone else using deep-learning AI, have been used to harass victims and extort money, including from minors. Malicious actors utilize content manipulation technologies and services to transform photographs and videos obtained from social media accounts or the open internet into sexually explicit images resembling the victim, which are then circulated on various platforms and websites.

The implications of AI-generated explicit imagery are far-reaching. Not only does it contribute to the normalization of child abuse, but it also hinders the identification of real victims in need of protection. The FBI’s warning sheds light on the concerning use of AI deepfakes in sextortion schemes. Victims, including minors, often remain unaware that their images have been manipulated and circulated until someone brings it to their attention.

In conclusion, while AI and its capabilities are advancing at an astonishing pace, it is critical to stay vigilant and address the potential risks and harmful consequences associated with the misuse of this technology, particularly in relation to the creation and dissemination of explicit images involving children. Law enforcement agencies, technology developers, and society as a whole must work together to combat these issues and protect the most vulnerable members of our communities.

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