Generative AI fraud

Generative AI refers to a category of artificial intelligence that can create new content—like text, images, audio, or video—rather than just analyzing existing data. These models are trained on massive datasets to learn patterns and structures that allow them to produce outputs that appear human-generated. Tools like ChatGPT, DALL·E, and Midjourney are examples of generative AI platforms.

A GAN is a specific type of generative model that consists of two neural networks: a generator and a discriminator. The generator tries to create realistic content, while the discriminator tries to distinguish fake from real. Over time, the generator gets better at fooling the discriminator, producing increasingly convincing synthetic outputs. GANs are often used in deepfake creation, synthetic identity fraud, and visual misinformation.

Besides GANs, other generative models include Variational Autoencoders (VAEs), diffusion models (used in tools like Stable Diffusion), and transformer-based models like GPT (for text) or MusicLM (for music). Each is optimized for different types of content generation, and unfortunately, all have been exploited in various forms of fraud—from AI-written phishing emails to synthetic audio impersonations used in scam calls.