- MIT researchers developed a new auditing method called Gaussian probing to detect if an AI model is fine-tuned for generating child sexual abuse material (CSAM) without producing any images, achieving 100% accuracy in tests.
- The method analyzes internal model adaptations from techniques like low-rank adaptation (LoRA) rather than outputs, bypassing legal and ethical issues of traditional output-based audits that require generating illegal content.
- This approach can be integrated into platforms like Hugging Face for automatic screening, offering a scalable, legally sound solution to prevent the spread of dangerous models, though it may not detect all CSAM generation methods.