arXiv:2607.05407v1 Announce Type: cross Abstract: Modern artificial intelligence (AI) systems present profound new risks to child safety. AI is increasingly being misused to create AI-generated child sexual abuse material, facilitate child sexual exploitation, and reduce barriers to harm. In this paper, we argue that protecting children from AI-facilitated sexual abuse requires new approaches to AI safety. Existing safety techniques assume data accessibility, transparency, and evaluation practices that are incompatible with the ethical and legal constraints surrounding child sexual abuse mater
The proliferation and increasing sophistication of generative AI models make the creation of malicious content, including AI-generated CSAM, an immediate and growing concern, necessitating proactive safety measures.
This highlights a critical and ethically charged problem at the intersection of AI development and societal safety, demanding urgent attention from policymakers, AI developers, and advocacy groups.
Existing AI safety frameworks, largely focused on benign applications, are now clearly inadequate for addressing the malicious misuse of generative AI for illegal and harmful content, requiring a paradigm shift in safety approaches.
- · Child protection organizations
- · AI safety researchers specializing in malicious use
- · Governments implementing new regulations
- · Ethical AI developers
- · AI developers ignoring safety implications
- · Platforms without robust content moderation
- · Users and children vulnerable to AI misuse
Increased pressure on AI developers to integrate 'safety by design' principles specifically targeting the prevention of illegal content generation.
Development of new AI-powered tools and techniques specifically designed to detect and counter AI-generated illicit content, potentially leading to an 'AI arms race' between creators and detectors.
Enhanced global cooperation on AI regulation and data sharing specifically for child protection, potentially setting precedents for broader international AI governance.
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Read at arXiv cs.AI